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CROP-seq analysis of TCR stimulation using the 10x Genomics platform

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NIAID Data Ecosystem2026-03-12 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE137554
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T cell receptor (TCR) signaling in Jurkat cells was investigated using the CROP-seq method for CRISPR single-cell sequencing. In CROP-seq, genetic perturbations are introduced into single cells in a pooled fashion, and single-cell RNA-seq is used to determine the transcriptional response to the CRISPR-induced perturbation in a large number of single cells in parallel. Importantly, the CROP-seq vector makes individual guide-RNAs detectable using standard single-cell RNA-seq technology. The dataset presented here is based on CROP-seq in combination with single-cell RNA-seq using the 10x Genomics v2 chemistry. It recapitulates a previously published CROP-seq dataset (Datlinger et al. 2017 Nature Methods; GEO: GSE92872) that used the Drop-seq protocol as the single-cell RNA-seq readout. Additional information on CROP-seq are available from the following website: http://crop-seq.computational-epigenetics.org/ . Cas9-expressing Jurkat cells were transduced using a lentiviral vector with a guide-RNA library targeting candidate regulators of TCR signaling, including signaling proteins and transcription factors. After 10 days of cell expansion with antibiotic selection for guide-RNA expressing cells, cells were stimulated with anti-CD3 and anti-CD28 antibodies (which induces potent TCR stimulation) or left untreated (control samples). Stimulated und unstimulated cells were subjected to single-cell RNA-seq using the Single Cell 3’ Library & Gel Bead Kit v2 (10x Genomics) followed by Illumina HiSeq 4000 sequencing. The sequencing data were analyzed using standard methods. To identify the guide-RNAs in each cell, a reference genome was created by extending the genome with the sequences of all used guide-RNAs.
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2020-09-03
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